The Brain’s Sequential Parallelism: Perceptual Decision-Making and Early Sensory Responses
Multi-stage decision tasks require the determination of intermediate results in order to perform consecutive decision steps. Electrophysiological recordings in sensory, parietal, and pre-frontal cortical areas have demonstrated that different response characteristics and timings at the neuron level provide key mechanisms to implement characteristic functionalities. We propose a hybrid neural model architecture that accounts for such findings and quantitatively reproduces the timing of such responses. We demonstrate by numerical simulations how the model accounts for feature-dependent decisions and how these are sequentialized during mutual interactions of pools of neurons in different cortical areas. Feedback from higher-level areas to early sensory stages of processing establishes a link between mechanisms involved in response integration and target selection to representations of sensory input.
KeywordsMulti-stage decision Electrophysiological recordings Hybrid neural model architecture
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- 5.Brosch, T., Neumann, H.: The Combination of HMAX and HOGs in an Attention Guided Framework for Object Localization. In: ICPRAM, vol. 2, pp. 281–288 (2012)Google Scholar
- 6.Mutch, J., Knoblich, U., Poggio, T.: CNS: a GPU-based Framework for Simulating Cortically-organized Networks. Tech. rep., MIT, Cambridge, MA, USA (2010)Google Scholar
- 8.Roelfsema, P.R.: Elemental Operations in Vision. TiCS 9(5), 226–233 (2005)Google Scholar
- 10.Zylberberg, A., Dehaene, S., Roelfsema, P.R., Sigman, M.: The Human Turing Machine: A Neural Framework for Mental Programs. TiCS 15(7), 293–300 (2011)Google Scholar
- 11.van der Velde, F., de Kamps, M.: Neural Blackboard Architectures of Combinatorial Structures in Cognition. Behav. Brain Sci. 29(1), 37–108 (2006)Google Scholar
- 12.Bouecke, J.D., Tlapale, E., Kornprobst, P., Neumann, H.: Neural Mechanisms of Motion Detection, Integration, and Segregation: From Biology to Artificial Image Processing Systems. EURASIP JASP 2011(6), 1–22 (2011)Google Scholar
- 13.Carpenter, G.A., Grossberg, S.: Pattern Recognition by Self-Organizing Neural Networks. A Bradford Book (1991)Google Scholar
- 15.Roitman, J.D., Shadlen, M.N.: Response of Neurons in the Lateral Intraparietal Area During a Combined Visual Discrimination Reaction Time Task. J. Neurosci. 22(21), 9475–9489 (2002)Google Scholar